Executing distributed applications on virtualized infrastructures specified with the VXDL language and managed by the HIPerNET framework

International audienceWith the convergence of computing and communication, and the expansion of cloud computing, new models and tools are needed to allow users to define, create, and exploit on-demand virtual infras- tructures within wide area distributed environments. Optimally design- ing customized virtual execution-infrastructure and executing them on a physical substrate remains a complex problem. This paper presents the VXDL language, a language for specifying and describing virtual infras- tructures and the HIPerNET framework to manage them. Based on the example of a specific biomedical application and workflow engine, this paper illustrates how VXDL enables to specify different customized vir- tual infrastructures and the HIPerNET framework to execute them on a distributed substrate. The paper presents experiments of the deploy- ment and execution of this application on different virtual infrastructures managed by our HIPerNet system. All the experiments are performed on the Grid'5000 testbed substrate

Exploring the Virtual Infrastructures as a Service concept with HIPerNET

With the expansion and convergence of communication and computing, dynamic provisioning of customized networking and processing infrastructures, as well as resource virtualization, are appealing concepts and technologies. Therefore, new models and tools are needed to allow users to create, trust and enjoy such on-demand virtual infrastructures within a wide area context. This research report presents the HIPerNET framework that we are designing and developing for creating, managing and controlling virtual infrastructures in the context of high-speed Internet. The key idea of this proposal is the combination of network- and system-virtualization associated with controlled resource reservation to provide fully isolated environments. HIPerNET's motivations and design principles are presented. We then examine specifically how this framework handles the virtual infrastructures, called Virtual Private eXecution Infrastructures (VPXI). To help specifying customized isolated infrastructures, HIPerNET relies on VXDL, a language for VPXI description and modeling which considers end-host resource as well as the virtual network topology interconnecting them, including virtual routers. We exemplify the VPXI specification, allocation and execution using a real large-scale distributed medical application. Experimental results obtained within the Grid'5000 testbed are presented and analyzed

Joint Elastic Cloud and Virtual Network Framework for Application Performance-cost Optimization

International audienceCloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. To adapt to the diversity of cloud infras- tructures and usage, new operation tools and models are needed. Estimating the amount of resources consumed by each application in particular is a difficult problem, both for end users who aim at minimizing their costs and infrastructure providers who aim at control- ling their resources allocation. Furthermore, network provision is generally not controlled on clouds. This paper describes a framework automating cloud resources allocation, deploy- ment and application execution control. It is based on a cost estimation model taking into account both virtual network and nodes managed by the cloud. The flexible provisioning of network resources permits the optimization of applications performance and infrastructure cost reduction. Four resource allocation strategies relying on the expertise that can be cap- tured in workflow-based applications are considered. Results of these strategies are confined virtual infrastructure descriptions that are interpreted by the HIPerNet engine responsible for allocating, reserving and configuring physical resources. The evaluation of this framework was carried out on the Aladdin/Grid'5000 testbed using a real application from the area of medical image analysis